Enhanced reduction of phenol content and toxicity in olive mill wastewaters by a newly isolated strain of Coriolopsis gallica

The search for novel microorganisms able to degrade olive mill wastewaters (OMW) and withstand the toxic effects of the initially high phenolic concentrations is of great scientific and industrial interest. In this work, the possibility of reducing the phenolic content of OMW using new isolates of fungal strains (Coriolopsis gallica, Bjerkandera adusta, Trametes versicolor, Trichoderma citrinoviride, Phanerochaete chrysosporium, Gloeophyllum trabeum, Trametes trogii, and Fusarium solani) was investigated. In vitro, all fungal isolates tested caused an outstanding decolorization of OMW. However, C. gallica gave the highest decolorization and dephenolization rates at 30 % v/v OMW dilution in water. Fungal growth in OMW medium was affected by several parameters including phenolic compound concentration, nitrogen source, and inoculum size. The optimal OMW medium for the removal of phenolics and color was with the OMW concentration (in percent)/[(NH₄)₂SO₄]/inoculum ratio of 30:6:3. Under these conditions, 90 and 85 % of the initial phenolic compounds and color were removed, respectively. High-pressure liquid chromatography analysis of extracts from treated and untreated OMW showed a clear and substantial reduction in phenolic compound concentrations. Phytotoxicity, assessed using radish (Raphanus sativus) seeds, indicated an increase in germination index of 23–92 % when a 30 % OMW concentration was treated with C. gallica in different dilutions (1/2, 1/4, and 1/8).

Investigating the real-world emission characteristics of light-duty gasoline vehicles and their relationship to local socioeconomic conditions in three communities in Los Angeles,California

This paper discusses results from a vehicular emissions research study of over 350 vehicles conducted in three communities in Los Angeles, CA, in 2010 using vehicle chase measurements. The study explores the real-world emission behavior of light-duty gasoline vehicles, characterizes real-world super-emitters in the different regions, and investigates the relationship of on-road vehicle emissions with the socioeconomic status (SES) of the region. The study found that in comparison to a 2007 earlier study in a neighboring community, vehicle emissions for all measured pollutants had experienced a significant reduction over the years, with oxides of nitrogen (NO_X) and black carbon (BC) emissions showing the largest reductions. Mean emission factors of the sampled vehicles in low-SES communities were roughly 2–3 times higher for NO_X, BC, carbon monoxide, and ultrafine particles, and 4–11 times greater for fine particulate matter (PM_2.5) than for vehicles in the high-SES neighborhood. Further analysis indicated that the emission factors of vehicles within a technology group were also higher in low-SES communities compared to similar vehicles in the high-SES community, suggesting that vehicle age alone did not explain the higher vehicular emission in low-SES communities.

Evaluation of the emission factor distribution found that emissions from 12% of the sampled vehicles were greater than five times the mean from all of the sampled fleet, and these vehicles were consequently categorized as “real-world super-emitters.” Low-SES communities had approximately twice as many super-emitters for most of the pollutants as compared to the high-SES community. Vehicle emissions calculated using model-year-specific average fuel consumption assumptions suggested that approximately 5% of the sampled vehicles accounted for nearly half of the total CO, PM_2.5, and UFP emissions, and 15% of the vehicles were responsible for more than half of the total NO_X and BC emissions from the vehicles sampled during the study.

Implications: This study evaluated the real-world emission behavior and super-emitter distribution of light-duty gasoline vehicles in California, and investigated the relationship of on-road vehicle emissions with local socioeconomic conditions. The study observed a significant reduction in vehicle emissions for all measured pollutants when compared to an earlier study in Wilmington, CA, and found a higher prevalence of high-emitting vehicles in low-socioeconomic-status communities. As overall fleet emissions decrease from stringent vehicle emission regulations, a small fraction of the fleet may contribute to a disproportionate share of the overall on-road vehicle emissions. Therefore, this work will have important implications for improving air quality and public health, especially in low-SES communities.     

Optimizing line intercept sampling and estimation for feral swine damage levels in ecologically sensitive wetland plant communities

Ecological sampling can be labor intensive, and logistically impractical in certain environments. We optimize line intercept sampling and compare estimation methods for assessing feral swine damage within fragile wetland ecosystems in Florida. Sensitive wetland sites, and the swine damage within them, were mapped using GPS technology. Evenly spaced parallel transect lines were simulated across a digital map of each site. The length of each transect and total swine damage under each transect were measured and percent swine damage within each site was estimated by two methods. The total length method (TLM) combined all transects as a single long transect, dividing the sum of all damage lengths across all transects by the combined length of all transect lines. The equal weight method (EWM) calculated the damage proportion for each transect line and averaged these proportions across all transects. Estimation was evaluated using transect spacings of 1, 3, 5, 10, 15, and 20 m. Based on relative root mean squared error and relative bias measures, the TLM produced higher quality estimates than EWM at all transect spacings. Estimation quality decreased as transect spacing increased, especially for TLM. Estimation quality also increased as the true proportion of swine damage increased. Diminishing improvements in estimation quality as transect spacings decreased suggested 5 m as an optimal tradeoff between estimation quality and labor. An inter-transect spacing of 5 m with TLM estimation appeared an optimal starting point when designing a plan for estimating swine damage, with practical, logistical, economic considerations determining final design details.     

The New Standard Environmental Inventory Questionnaire for Estimation of Indoor Concentrations

Several investigators have developed indoor air quality questionnaires for use in field studies. The approach used in many of them have numerous features in common, but most of them are unique in their content (wording, format, item selection). It is thought that indoor air quality research could be greatly advanced if the primary or fundamental questions and instruments could be consolidated. The use of a basic set of "standard" questions would permit intercomparison of results from different research studies. It is generally agreed that environmental inventory questionnaires (EIQ) help to classify, at least in screening, relative concentration estimates, which precede exposure estimation. Thus, such instruments are not equivalent to monitoring for exposure assessment. However, data linkage and mega data bases are important for some comparative analyses of exposure assessment and exposure-response relationships. Standard instruments such as the EIQ are useful as a screening device to precede other tests to allow identification of potentially high exposure situations. They can also amplify information from other tests. General usage of standard questionnaires and protocols can lead to cumulative improvements in data collection, specificity and effectiveness. This has been the rationale for the present efforts by investigators to form a standardized environmental inventory questionnaire, under the auspices of the U.S. Environmental Protection Agency (EPA), Gas Research Institute (GRI), and Electric Power Research Institute (EPRI).     

The Use of Ambient Measurements To Identify which Precursor Species Limit Aerosol Nitrate Formation

ABSTRACT

A thermodynamic equilibrium model was used to investigate the response of aerosol NO₃ to changes in concentrations of HNO₃, NH₃, and H₂SO₄. Over a range of temperatures and relative humidities (RHs), two parameters provided sufficient information for indicating the qualitative response of aerosol NO₃. The first was the excess of aerosol NH₄ ⁺ plus gas-phase NH₃ over the sum of HNO₃, particulate NO₃, and particulate SO₄ ^2- concentrations. The second was the ratio of particulate to total NO₃ concentrations. Computation of these quantities from ambient measurements provides a means to rapidly analyze large numbers of samples and identify cases in which inorganic aerosol NO₃ formation is limited by the availability of NH₃. Example calculations are presented using data from three field studies. The predictions of the indicator variables and the equilibrium model are compared.     

A synthesis of progress and uncertainties in attributing the sources of mercury in deposition

A panel of international experts was convened in Madison, Wisconsin, in 2005, as part of the 8th International Conference on Mercury as a Global Pollutant. Our charge was to address the state of science pertinent to source attribution, specifically our key question was: "For a given location, can we ascertain with confidence the relative contributions of local, regional, and global sources, and of natural versus anthropogenic emissions to mercury deposition?" The panel synthesized new research pertinent to this question published over the past decade, with emphasis on four major research topics: long-term anthropogenic change, current emission and deposition trends, chemical transformations and cycling, and modeling and uncertainty. Within each topic, the panel drew a series of conclusions, which are presented in this paper. These conclusions led us to concur that the answer to our question is a "qualified yes," with the qualification being dependent upon the level of uncertainty one is willing to accept. We agreed that the uncertainty is strongly dependent upon scale and that our question as stated is answerable with greater confidence both very near and very far from major point sources, assuming that the "global pool" is a recognizable "source." Many regions of interest from an ecosystem-exposure standpoint lie in between, where source attribution carries the greatest degree of uncertainty.     

Speciation of zinc in contaminated soils

The chemical speciation of zinc in soil solutions is critical to the understanding of its bioavailability and potential toxic effects. We studied the speciation of Zn in soil solution extracts from 66 contaminated soils representative of a wide range of field conditions in both North America and Europe. Within this dataset, we evaluated the links among the dissolved concentrations of zinc and the speciation of Zn(2+), soil solution pH, total soil Zn, dissolved organic matter (DOM), soil organic matter (SOM) and the concentrations of different inorganic anions. The solid-liquid partitioning coefficient (K(d)) for Zn ranged from 17 to 13,100Lkg(-1) soil. The fraction of dissolved Zn bound to DOM varied from 60% to 98% and the soil solution free Zn(2+) varied from 40% to 60% of the labile Zn. Multiple regression equations to predict free Zn(2+), dissolved Zn and the solid-liquid partitioning of Zn are given for potential use in environmental fate modeling and risk assessment. The multiple regressions also highlight some of the most important soil properties controlling the solubility and chemical speciation of zinc in contaminated soils.     

Assessing energy, environmental, and economic tradeoffs in intermodal freight transportation

This paper presents an energy and environmental network analysis model to explore tradeoffs associated with freight transport. The geospatial model uses an intermodal network built by the authors to connect various modes (rail, road, water) via intermodal terminals. Routes along the network are characterized not only by temporal and distance attributes, but also by cost, energy, and emissions attributes (including emissions of carbon dioxide, particulate matter, sulfur oxides, volatile organic compounds, and oxides of nitrogen). Decision-makers can use the model to explore tradeoffs among alternative route selection across different modal combinations, and to identify optimal routes for objectives that feature energy and environmental parameters (e.g., minimize carbon dioxide emissions). The model is demonstrated with three case studies of freight transport along the U.S. eastern seaboard.     

A condition metric for Eucalyptus woodland derived from expert evaluations

The evaluation of ecosystem quality is important for land‐management and land‐use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert‐evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers’ evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data‐driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real‐world contexts. We believe our approach is applicable to any ecosystem.     

Participatory GIS and its application in governance: the example of air quality and the implications for noise pollution

Abstract

Participatory GIS (geographic information systems) is designed to use community mapping exercises to produce spatial representations of local knowledge. The ideals of Participatory GIS revolve around the concept of public participation in the use of spatial data leading to increased community involvement in policy-setting and decision-making (Weiner et al., Community participation and geographic information systems, in: Craig et al., Community participation and geographic information systems, London: Taylor & Francis, 2002). This paper reports on findings from two case studies, one relating to assessments of air quality and how Participatory GIS has been used in the UK to improve local government policy, and the second on assessments of noise pollution. It concludes by discussing a caveat on the use of Participatory GIS for environmental governance, which is that, ideally, only issues on which participants are likely to have direct experiential knowledge should be targeted.